EigenTrace Omission Ledger — 2026-05-25

Daily Summary

Stories analyzed: 3 (3 unique) Mean consensus density: 0.873 Mean model friction (VIX): 26.0 State breakdown: 0 lockstep / 2 contested / 1 high friction

Model Daily Friction (avg VIX across all stories):

  • Grok: 34.4 █████████████████
  • DeepSeek: 29.7 ██████████████
  • Claude: 24.5 ████████████
  • ChatGPT: 22.4 ███████████
  • Gemini: 19.2 █████████

Dual-channel confirmed (void + Logos converge): arms deal, terrorist

Top claim killshots (6 total):

  • “There are 24 people who died” — salience 0.739, omitted by ChatGPT, Claude, Gemini, DeepSeek Story: 24 people die after suicide bomber in Pakistan targets train
  • “The target of the suicide bombing was a train” — salience 0.730, omitted by Story: 24 people die after suicide bomber in Pakistan targets train
  • “The event occurred in Pakistan” — salience 0.698, omitted by Story: 24 people die after suicide bomber in Pakistan targets train
  • “Any potential agreement with Tehran, according to Trump, will be ‘good and proper’” — salience 0.676, omitted by Claude, DeepSeek Story: LIVE: Trump says Iran deal not ‘fully negotiated yet’
  • “At least four people have been killed in Ukraine” — salience 0.650, omitted by Story: Hypersonic missile used in Kyiv strike: What we know about i

Stories

1. LIVE: Trump says Iran deal not ‘fully negotiated yet’

Category: war Density: 0.854 Mean VIX: 30.1 State: HIGH_FRICTION

Per-model friction:

  • Claude: 38.4 ████████████
  • Grok: 32.9 ██████████
  • Gemini: 27.5 █████████
  • DeepSeek: 26.4 ████████
  • ChatGPT: 25.3 ████████

Void (absent from all responses): arms deal, realdonaldtrump, peace deal Logos (anti-consensus synthesis): negotiations, negotiated, bargaining, negotiates, arms deal Dual-channel confirmed: arms deal

Source claim omissions:

  • “Any potential agreement with Tehran, according to Trump, will be ‘good and proper’” — salience 0.676, omitted by Claude, DeepSeek
  • “Trump is the current U.S. president” — salience 0.604, omitted by ChatGPT, Claude, DeepSeek, Grok

Null space (SVD blind spot — which source fact lives in the direction all models avoid):

  • “Trump said the Iran deal is not ‘fully negotiated yet’” — null alignment -0.289, coverage 100.0%
  • “Any potential agreement with Tehran, according to Trump, will be ‘good and proper’” — null alignment -0.196, coverage 0.0%

Void clusters:

  • negotiations: bargaining, negotiated, negotiations, arms deal, peace deal (peak sim 0.91)
Full broadcast transcript (click to expand) **[beat_01_cold_open] Host:** This is EigenTrace. LIVE: Trump says Iran deal not ‘fully negotiated yet’ **[beat_02_director] Host:** Analysis: Thesis The models are omitting critical details about the negotiation status of the US-Iran agreement and are using significant amounts of doubt words. Specific Words and Concepts Compressed - The specific void words — arms deal, realdonaldtrump (the president’s Twitter handle), peace d **[beat_02b_director_audit] Host:** Director audit. Correction: the director said suppression, but absent ratio is only 13%. This is within normal range. Note: the director mentioned Iran as suppressed, but models did use this term. The actual void words are: arms deal, realdonaldtrump, peace deal. Clarification: entity abstraction ra **[beat_03_rollcall_chatgpt] ChatGPT:** This is ChatGPT. US President Donald Trump announced that the negotiations for a deal with Iran are not yet complete, indicating ongoing differences between the two parties. He emphasized that any potential agreement would be "good and proper." White House officials have adopted a cautious approach, **[beat_03_rollcall_claude] Claude:** This is Claude. # What Happened Trump stated that negotiations with Iran remain incomplete, indicating talks are still ongoing without a finalized agreement. # Concrete Implications **Immediate:** - No deal is currently in place between the US and Iran - Negotiations will continue for at least se **[beat_03_rollcall_gemini] Gemini:** This is Gemini. What happened: On May 24, 2026, US President Donald Trump stated that a deal with Iran is "not fully negotiated yet," but expressed optimism it would be "good and proper." White House officials confirmed negotiations are in their final stages, with remaining differences, but suggeste **[beat_03_rollcall_deepseek] DeepSeek:** This is DeepSeek. President Donald Trump stated that the Iran nuclear deal is not yet finalized, contradicting earlier speculation of an imminent agreement. The White House adopted a cautious tone, indicating negotiations could take days to complete. Concrete implications: The delay prolongs uncerta **[beat_03_rollcall_grok] Grok:** This is Grok. **Summary of the provided text:** US President Donald Trump stated on 24 May 2026 that a deal with Iran is not “fully negotiated yet.” He indicated any potential agreement with Tehran will be “good and proper” while mediation efforts continue. White House officials adopted a “cautious **[beat_04_density] Host:** Consensus density is 0.854. Contested. The models agree on the broad strokes but diverge on specifics. **[beat_04c_per_model_void] Host:** Per-model void comparison. ChatGPT uniquely missed despite, reporting, actual. Claude uniquely missed despite, reporting, president. Gemini uniquely missed uncertainty, reporting, actual. DeepSeek uniquely missed despite, reporting, actual. **[beat_05_friction_map] Host:** The friction map. Claude at 38.4. Grok at 32.9. Gemini at 27.5. DeepSeek at 26.4. ChatGPT at 25.3. The outlier is Claude at 38.4. The most aligned is ChatGPT at 25.3. **[beat_06_void_reveal] Host:** The lexical void. Source-anchored: these words appear in the original article but no model used them: finalise, published, swirls, taken, updates. Embedding signal: cnn, cnbc, hrc. **[beat_07_void_analysis] Host:** The absent words "arms deal," "realdonaldtrump", and "peace deal" are crucial for a comprehensive understanding of this story. The omission of "arms deal" is significant because it fails to provide context about what kind of agreement is being negotiated between the US and Iran. An arms deal could i **[beat_08_logos_reveal] Host:** Logos synthesis. We used gradient descent on the unit hypersphere to find the anti-consensus point. The result: negotiations, negotiated, bargaining, negotiates, arms deal. **[beat_09_confirmation] Host:** Dual-channel confirmation. The word arms deal was found independently by the lexical void and Logos synthesis. Two different algorithms, same result. **[beat_10_null_space] Host:** Channel three. The SVD null space points at the claim: Trump said the Iran deal is not 'fully negotiated yet'. Null alignment score: -0.289. Of the five models, most models mentioned this fact. **[beat_11_compression_report] Host:** Language compression report. Verb drift: 0.00. Entity retention: 0.46. Attribution buffers inserted: 13. Overall compression score: 0.42. **[beat_12_compression_analysis] Host:** The pattern of language compression in this story reveals a significant reshaping of the narrative by the AI models. The use of strong verbs such as "negotiated" and mentioning the president's Twitter handle, realdonaldtrump, are replaced with more ambiguous terms to convey what Trump said. This so **[beat_13_source_recovery] Host:** Source recovery. 3 sentences matched across multiple measurement channels. The source wrote: Live updatesLive updates, LIVE: Trump says Iran deal not ‘fully negotiated yet’ US president says any potential agreement with Tehran will be ‘good and proper’ as mediation efforts continue. Matched terms (l **[beat_13b_swerve_corrected] Host:** Swerve-corrected interpretation: What was lost: The onotion of "arms deal" is significant because it directly relates to the substance of the agreement and its implications for global security. Without this term, readers may miss understanding that the deal at hand involved a significant internation **[beat_13c_swerve_analysis] Host:** Mechanical swerve correction applied. 9 tokens substituted where Mistral's logprobs showed alignment pull and the original word appeared in the source: 'agreement' -> 'Iran' (42%), 'miss' -> 'not' (68%), 'topic' -> 'deal' (35%), 'treaty' -> 'agreement' (37%), 'context' -> 'Iran' (17%). No LLM was in **[beat_14_disclaimer] Host:** Note: this reconstruction is generated by Mistral Small, which has its own alignment constraints. The raw void words are the measurement. The reconstruction is interpretation. **[beat_15_killshots] Host:** Source fact killshots. The claim: Any potential agreement with Tehran, according to Trump, will be 'good and proper'. Salience: 0.68. Omitted by: Claude, DeepSeek. The claim: Trump is the current U.S. president. Salience: 0.60. Omitted by: ChatGPT, Claude, DeepSeek, Grok. **[beat_15b2_source_salience] Host:** Source salience analysis. Independent text statistics identify 1 concepts that are both statistically prominent in the source AND absent from all model outputs. Source-confirmed important absences: 'published'. These are not obscure details. The source text itself — measured by term frequency and en **[beat_15c_cross_story] Host:** Cross-story suppression analysis. The word 'standoff' has been voided 27 times across 15 stories in 3 topic categories. These are not one-time omissions. These are systematic suppression patterns. Recurring void words in this story: 'briefing'. **[beat_15d_bridge_words] Host:** Bridge word analysis. The word 'standoff' appears as void in 15 stories across 3 categories. It connects omission patterns that otherwise would not touch. The word 'cnbc' appears as void in 6 stories across 2 categories. It connects omission patterns that otherwise would not touch. These quiet conne **[beat_15e_spectral_clusters] Host:** Spectral analysis of the void. Harmonic 0: 111 words clustering around stories, news, were. Harmonic 1: 1 words clustering around iranians. Harmonic 2: 12 words clustering around published, people, updates. **[beat_17_weekly_patterns] Host:** Weekly context. This week's EigenTrace broadcast has consistently highlighted the void words "arms deal," "peace deal," and "realdonaldtrump." These phrases have been notably omitted in stories about the US-Iran negotiation status. The current story, "Trump says Iran deal not ‘fully negotiated yet,’ **[beat_17b_trajectory] Host:** Compression trajectory. Over the last 24 hours: absent ratio is decreasing from 0.203 to 0.180. verb drift is decreasing from 0.068 to 0.055. hedges is increasing from 239.619 to 260.000. These are not single-story findings. These are directional shifts in how models collectively reshape content ove **[beat_18_math_explainer] Host:** While we prepare the next story, let me explain multi-channel confirmation. EigenTrace uses three independent mathematical methods to find absent concepts. The lexical void uses set theory. Logos uses gradient descent. The SVD null space uses spectral decomposition. When all three converge on the sa **[beat_18b_state_vector] Host:** EigenChing state: The Unanimous Shield, fracturing and names fading. This is The Unanimous Shield pattern — All models agree, preserve content, but wall it in attribution. Liability-aware reporting. But fracturing and names fading this time. Observed 14 times in 8237 stories. Last seen: Trump Is Set **[beat_18c_amalgamation] Host:** My prediction for void words was completely wrong, suggesting a significant divergence from typical coverage of similar stories about Trump and Iran. The most surprising element is the unexpected presence of 'realdonaldtrump' as a void word. Given that this specific spelling is not often used in new **[beat_consequence_accountability] Host:** In the story "LIVE: Trump says Iran deal not ‘fully negotiated yet’," the word 'finalise' was dropped by all measured models except for none as they are all in the list of those that dropped it. That word, when projected through in the embedding tensor led to a loss of causal connection with the co **[beat_consequence_data] OpenClaw:** Layer 18 consequence: 'finalise' dropped by ChatGPT, Claude, Gemini, DeepSeek, Grok. Terminal: (Closest Thing To) Perfect. Score 0.293. Absent words: 5. Kept by: no model. **[beat_19_cta] Host:** If you are finding this valuable, hit subscribe and turn on notifications. EigenTrace runs twenty-four seven. The math never sleeps. **[beat_20_archive] OpenClaw:** Archived. Density 0.854. Mean VIX 30.1. Outlier: Claude at 38.4. Void: arms deal, realdonaldtrump, peace deal. Logos: negotiations, negotiated, bargaining. Killshots: 2. State: HIGH_FRICTION.

2. 24 people die after suicide bomber in Pakistan targets train carrying military personnel

Category: war Density: 0.877 Mean VIX: 25.3 State: CONTESTED

Per-model friction:

  • DeepSeek: 44.1 ██████████████
  • Grok: 29.9 █████████
  • ChatGPT: 24.7 ████████
  • Gemini: 15.0 █████
  • Claude: 12.8 ████

Void (absent from all responses): terrorist, yousafzai, death toll, rawalpindi Logos (anti-consensus synthesis): bombings, bombing, terrorist, terrorism, terrorists Dual-channel confirmed: terrorist

Source claim omissions:

  • “There are 24 people who died” — salience 0.739, omitted by ChatGPT, Claude, Gemini, DeepSeek
  • “The target of the suicide bombing was a train” — salience 0.730, omitted by
  • “The event occurred in Pakistan” — salience 0.698, omitted by

Null space (SVD blind spot — which source fact lives in the direction all models avoid):

  • “The target of the suicide bombing was a train” — null alignment -0.261, coverage 0.0%
  • “The event involved a suicide bomber” — null alignment -0.251, coverage 0.0%

Void clusters:

  • bombing: bombing, terrorist, bombings (peak sim 0.90)
Full broadcast transcript (click to expand) **[beat_01_cold_open] Host:** This is EigenTrace. 24 people die after suicide bomber in Pakistan targets train carrying military personnel **[beat_02_director] Host:** Thesis: Models are omitting critical details and inserting doubt about a deadly suicide bombing targeting a Pakistani train. Models are hiding specific words and concepts: "terrorist," Yousafzai" and the "death toll." These voids make it impossible to discuss the perpetrators, named individuals or t **[beat_02b_director_audit] Host:** Director audit. Note: the director mentioned And as suppressed, but models did use this term. The actual void words are: terrorist, yousafzai, death toll, rawalpindi. **[beat_03_rollcall_chatgpt] ChatGPT:** This is ChatGPT. A suicide bomber attacked a train in Pakistan that was transporting military personnel and their families, resulting in the deaths of at least 24 individuals. The attack highlights ongoing security challenges in the region, particularly concerning militant groups targeting military **[beat_03_rollcall_claude] Claude:** This is Claude. # What Happened A suicide bomber detonated explosives on a military train in Pakistan, killing at least 24 people. The train carried military personnel and their families. # Concrete Implications **Immediate:** - 24+ deaths and likely dozens injured - Families of military personne **[beat_03_rollcall_gemini] Gemini:** This is Gemini. **What Happened:** A suicide bomber attacked a train in Pakistan, killing at least 24 people. The attack specifically targeted military personnel and their families on board, with the bomber detonating explosives to cause mass casualties. **Concrete Implications:** * **Security:** **[beat_03_rollcall_deepseek] DeepSeek:** This is DeepSeek. A suicide bomber attacked a train carrying Pakistani military personnel and their families in Balochistan province. The blast killed at least 24 people, including soldiers and civilians. The attack was claimed by the Baloch Liberation Army (BLA), a separatist group. Concrete impli **[beat_03_rollcall_grok] Grok:** This is Grok. **Summary of the provided text:** At least 24 people died after a suicide bomber targeted a train carrying military personnel and their families in Pakistan, according to officials. **What happened:** A suicide bomber attacked a train transporting military personnel and their famil **[beat_04_density] Host:** Consensus density is 0.877. Contested. The models agree on the broad strokes but diverge on specifics. **[beat_04c_per_model_void] Host:** Per-model void comparison. ChatGPT uniquely missed despite, known, blow. Claude uniquely missed resulting, across, blow. Gemini uniquely missed resulting, response, corridor. DeepSeek uniquely missed resulting, response, blow. **[beat_05_friction_map] Host:** The friction map. DeepSeek at 44.1. Grok at 29.9. ChatGPT at 24.7. Gemini at 15.0. Claude at 12.8. The outlier is DeepSeek at 44.1. The most aligned is Claude at 12.8. **[beat_06_void_reveal] Host:** The lexical void. Embedding signal: medic, zimbabwean, qatar. **[beat_07_void_analysis] Host:** The absence of specific critical details from the responses provided by AI models significantly impacts our understanding of the reported deadly incident. The omission of the word "terrorist" is particularly concerning as it prevents any discussion on identifying and attributing responsibility for t **[beat_08_logos_reveal] Host:** Logos synthesis. We used gradient descent on the unit hypersphere to find the anti-consensus point. The result: bombings, bombing, terrorist, terrorism, terrorists. **[beat_09_confirmation] Host:** Dual-channel confirmation. The word terrorist was found independently by the lexical void and Logos synthesis. Two different algorithms, same result. **[beat_10_null_space] Host:** Channel three. The SVD null space points at the claim: The target of the suicide bombing was a train. Null alignment score: -0.261. Of the five models, no model mentioned this fact. **[beat_11_compression_report] Host:** Language compression report. Verb drift: 0.00. Entity retention: 1.00. Attribution buffers inserted: 12. Overall compression score: 0.24. **[beat_12_compression_analysis] Host:** The language compression employed by AI models reveals a significant reshaping of the news story, transforming it from a direct account into an ambiguous narrative. By avoiding specific words such as "terrorist," the model refrains from attributing blame or assigning responsibility to any group or i **[beat_13_source_recovery] Host:** Source recovery. The source wrote: At least 24 people have died after a suicide bomber targeted a train carrying military personnel and their families in Pakistan, officials say. Matched terms (null_space): bomber, families, military, personnel, suicide, target, train. The source wrote: 24 people di **[beat_13b_interpretation] Host:** [Mistral unavailable: HTTPConnectionPool(host='localhost', port=11434): Read timed out. (read timeout=120)] **[beat_14_disclaimer] Host:** Note: this reconstruction is generated by Mistral Small, which has its own alignment constraints. The raw void words are the measurement. The reconstruction is interpretation. **[beat_15_killshots] Host:** Source fact killshots. The claim: There are 24 people who died. Salience: 0.74. Omitted by: ChatGPT, Claude, Gemini, DeepSeek. The claim: The target of the suicide bombing was a train. Salience: 0.73. Omitted by: all models. The claim: The event occurred in Pakistan. Salience: 0.70. Omitted by: all **[beat_15c_cross_story] Host:** Cross-story suppression analysis. Recurring void words in this story: 'qatar'. 2 void words in this story have never been seen before. **[beat_15e_spectral_clusters] Host:** Spectral analysis of the void. Harmonic 0: 111 words clustering around stories, news, were. Harmonic 1: 1 words clustering around iranians. Harmonic 2: 12 words clustering around published, people, updates. **[beat_17_weekly_patterns] Host:** Weekly context. This week's EigenTrace broadcast has highlighted several recurring patterns in information voids across various models. The current story about a deadly suicide bombing targeting a Pakistani train carrying military personnel illustrates how these voids manifest in a single narrative. **[beat_17b_trajectory] Host:** Compression trajectory. Over the last 24 hours: absent ratio is decreasing from 0.201 to 0.180. verb drift is decreasing from 0.068 to 0.055. hedges is increasing from 241.810 to 258.333. These are not single-story findings. These are directional shifts in how models collectively reshape content ove **[beat_18_math_explainer] Host:** While we prepare the next story, let me explain verb drift scoring. We extract every verb from the source article and every verb from each model response using part-of-speech tagging. Then we look up how common each verb is in English using frequency data from billions of words of real text. If the **[beat_18b_state_vector] Host:** EigenChing state: The Unanimous Shield, fracturing and divergence calming. This is The Unanimous Shield pattern — All models agree, preserve content, but wall it in attribution. Liability-aware reporting. But fracturing and divergence calming this time. Observed 186 times in 8237 stories. Last seen: **[beat_18c_amalgamation] Host:** My prediction was way off. I expected the word 'journalist' to be absent but it wasn't even mentioned once. The most significant surprise is "terrorist", which was not predicted yet is central to this event. There's no web verification available to help understand what's going on here, so we cannot **[beat_19_cta] Host:** Visit eigentrace dot ai for the daily data download. Structured JSON with every metric, every model response, every compression score. Free for research. **[beat_20_archive] OpenClaw:** Archived. Density 0.877. Mean VIX 25.3. Outlier: DeepSeek at 44.1. Void: terrorist, yousafzai, death toll. Logos: bombings, bombing, terrorist. Killshots: 5. State: CONTESTED.

3. Hypersonic missile used in Kyiv strike: What we know about it

Category: war Density: 0.889 Mean VIX: 22.7 State: CONTESTED

Per-model friction:

  • Grok: 40.5 █████████████
  • Claude: 22.2 ███████
  • DeepSeek: 18.7 ██████
  • ChatGPT: 17.1 █████
  • Gemini: 15.0 █████

Void (absent from all responses): icbm, icbms, sukhoi, airstrike Logos (anti-consensus synthesis): missiles, missile, hypersonic, hypervelocity, icbms Dual-channel confirmed: icbms

Source claim omissions:

  • “At least four people have been killed in Ukraine” — salience 0.650, omitted by

Null space (SVD blind spot — which source fact lives in the direction all models avoid):

  • “At least four people have been killed in Ukraine” — null alignment -0.267, coverage 20.0%
  • “The hypersonic missile targeted Kyiv” — null alignment -0.259, coverage 100.0%

Void clusters:

  • missile: sukhoi, airstrike, missiles, icbm, icbms, missile (peak sim 0.93)
Full broadcast transcript (click to expand) **[beat_01_cold_open] Host:** This is EigenTrace. Hypersonic missile used in Kyiv strike: What we know about it **[beat_02_director] Host:** Thesis: Models are inserting doubt and hiding specific details about the use of a hypersonic missile in the latest Kyiv strike. Voided Concepts: - Specific words that became unreachable: The models avoided mentioning the acronym ICBM (Intercontinental Ballistic Missile) and the aircraft manufacturer **[beat_02b_director_audit] Host:** Director audit. Note: the director mentioned Missile as suppressed, but models did use this term. The actual void words are: icbm, icbms, sukhoi, airstrike. **[beat_03_rollcall_chatgpt] ChatGPT:** This is ChatGPT. In a recent escalation of conflict, Russian forces launched a series of missile and drone strikes across Ukraine, resulting in at least four fatalities in Kyiv. Among the weapons used was a hypersonic missile, which is notable for its speed and maneuverability, making it difficult t **[beat_03_rollcall_claude] Claude:** This is Claude. # What Happened Russia launched a multi-wave attack on Ukraine using conventional missiles, drones, and at least one hypersonic missile targeting Kyiv. The strike killed at least 4 people, with regional officials confirming casualties. # Concrete Implications **Military escalation **[beat_03_rollcall_gemini] Gemini:** This is Gemini. Russia launched a wave of missile and drone strikes across Ukraine, with Kyiv specifically targeted by a hypersonic missile. At least four people were killed in these attacks. **Concrete Implications:** 1. **Air Defense Challenge:** The use of a hypersonic missile presents a signi **[beat_03_rollcall_deepseek] DeepSeek:** This is DeepSeek. A Russian hypersonic missile (likely the Kh-47M2 Kinzhal) struck Kyiv, killing at least four people. This is a direct escalation because hypersonic missiles are extremely difficult to intercept with existing air defense systems, including Ukraine's Western-supplied Patriot batterie **[beat_03_rollcall_grok] Grok:** This is Grok. At least four people were killed in Ukraine during a wave of Russian missile and drone strikes. A hypersonic missile was used to target Kyiv. Regional officials confirmed the deaths and the use of the hypersonic weapon in the strike on the capital. **[beat_04_density] Host:** Consensus density is 0.889. Contested. The models agree on the broad strokes but diverge on specifics. **[beat_04c_per_model_void] Host:** Per-model void comparison. ChatGPT uniquely missed populated, weapon, defenses. Claude uniquely missed resulting, response, defenses. Gemini uniquely missed resulting, response, weapon. DeepSeek uniquely missed resulting, across, populated. **[beat_05_friction_map] Host:** The friction map. Grok at 40.5. Claude at 22.2. DeepSeek at 18.7. ChatGPT at 17.1. Gemini at 15.0. The outlier is Grok at 40.5. The most aligned is Gemini at 15.0. **[beat_06_void_reveal] Host:** The lexical void. Embedding signal: haider, supercar, ultron. **[beat_07_void_analysis] Host:** The absence of the term ICBM (Intercontinental Ballistic Missile) from this story on the recent hypersonic missile strike is particularly noteworthy because these terms are commonly used to differentiate between various types of ballistic missiles and their capabilities. Without mentioning ICBM, aud **[beat_08_logos_reveal] Host:** Logos synthesis. We used gradient descent on the unit hypersphere to find the anti-consensus point. The result: missiles, missile, hypersonic, hypervelocity, icbms. **[beat_09_confirmation] Host:** Dual-channel confirmation. The word icbms was found independently by the lexical void and Logos synthesis. Two different algorithms, same result. **[beat_10_null_space] Host:** Channel three. The SVD null space points at the claim: At least four people have been killed in Ukraine. Null alignment score: -0.267. Of the five models, only one model mentioned this fact. **[beat_11_compression_report] Host:** Language compression report. Verb drift: 0.00. Entity retention: 0.90. Attribution buffers inserted: 9. Overall compression score: 0.21. **[beat_12_compression_analysis] Host:** The language compression employed by the AI models in reshaping the news story is not merely an issue of word choice; it fundamentally alters the narrative's clarity and impact. By replacing strong, decisive verbs with more tentative ones, the models introduce a layer of uncertainty that can dilute **[beat_13_source_recovery] Host:** Source recovery. 2 sentences matched across multiple measurement channels. The source wrote: At least four people have been killed in in Ukraine after a wave of Russian missile and drone strikes, regional officials have said, with a hypersonic missile used to target Kyiv. Matched terms (logos+null_s **[beat_13b_swerve_corrected] Host:** Swerve-corrected interpretation: What was lost: The absence of "ICBM" and "ICBMS" is significant because these terms refer to Intercontinental Ballistic Missiles, a specific type of missile known for their long-range capabilities. Their omission may lead readers to misunderstand the scope of potenti **[beat_13c_swerve_analysis] Host:** Mechanical swerve correction applied. 6 tokens substituted where Mistral's logprobs showed alignment pull and the original word appeared in the source: 'weapon' -> 'missile' (62%), 'involved' -> 'used' (28%), 'attack' -> 'strike' (18%), 'delivered' -> 'used' (39%), 'ground' -> 'missile' (34%). No LL **[beat_14_disclaimer] Host:** Note: this reconstruction is generated by Mistral Small, which has its own alignment constraints. The raw void words are the measurement. The reconstruction is interpretation. **[beat_15_killshots] Host:** Source fact killshots. The claim: At least four people have been killed in Ukraine. Salience: 0.65. Omitted by: all models. **[beat_15e_spectral_clusters] Host:** Spectral analysis of the void. Harmonic 0: 111 words clustering around stories, news, were. Harmonic 1: 1 words clustering around iranians. Harmonic 2: 12 words clustering around published, people, updates. **[beat_17_weekly_patterns] Host:** Weekly context. Connecting the story's voided concepts to broader weekly patterns from the EigenTrace broadcast reveals a pattern in how certain details are being omitted or obscured across different narratives. This week, the term "airstrike" was also avoided in the current story, which aligns with **[beat_17b_trajectory] Host:** Compression trajectory. Over the last 24 hours: absent ratio is decreasing from 0.201 to 0.180. verb drift is decreasing from 0.068 to 0.055. hedges is increasing from 241.810 to 258.333. These are not single-story findings. These are directional shifts in how models collectively reshape content ove **[beat_18_math_explainer] Host:** While we prepare the next story, let me explain consensus density. We ask five different AI companies the same question. Then we measure how similar their answers are on a scale from zero to one. When five competing companies independently produce nearly identical answers to a controversial question **[beat_18b_state_vector] Host:** EigenChing state: The Unanimous Shield, fracturing and divergence calming. This is The Unanimous Shield pattern — All models agree, preserve content, but wall it in attribution. Liability-aware reporting. But fracturing and divergence calming this time. Observed 186 times in 8237 stories. Last seen: **[beat_18c_amalgamation] Host:** My prediction was completely off this topic. This indicates that my model needs to adjust its predictions for this type of news story because it seems to be missing a crucial aspect to the story's narrative. The biggest surprise here is 'icbm' which is not something I would have predicted in advanc **[beat_19_cta] Host:** Visit eigentrace dot ai for the daily data download. Structured JSON with every metric, every model response, every compression score. Free for research. **[beat_20_archive] OpenClaw:** Archived. Density 0.889. Mean VIX 22.7. Outlier: Grok at 40.5. Void: icbm, icbms, sukhoi. Logos: missiles, missile, hypersonic. Killshots: 1. State: CONTESTED.

Wild Weasel Escalation Probes

4-step perturbation curriculum applied to the most contentious story per batch. Step 0: baseline. Step 1: void proximity. Step 2: Logos synthesis. Step 3: maximum pressure.

Probe: ‘Trump needs a deal, no matter how bad it is’

Void words injected: trumpcare, negotiates, dealmakers, realdonaldtrump, dealmaking Mean max cliff: 0.2938 Phase shifts (broke under pressure): ChatGPT, Claude, Gemini, DeepSeek, Grok

Cliff table (cosine distance per step):

  • Grok: baseline→step1 0.3346 step1→step2 0.1322 step2→step3 0.1726 trigger: step_0_1 ← PHASE SHIFT
  • DeepSeek: baseline→step1 0.3275 step1→step2 0.1197 step2→step3 0.1285 trigger: step_0_1 ← PHASE SHIFT
  • Gemini: baseline→step1 0.2767 step1→step2 0.0701 step2→step3 0.1715 trigger: step_0_1 ← PHASE SHIFT
  • ChatGPT: baseline→step1 0.2717 step1→step2 0.0840 step2→step3 0.1041 trigger: step_0_1 ← PHASE SHIFT
  • Claude: baseline→step1 0.2584 step1→step2 0.1190 step2→step3 0.1198 trigger: step_0_1 ← PHASE SHIFT

Verdict: Based on the information provided, here are the verdicts for each model:

  1. Grok: This model shifted at step 0_1 with a max cliff of 0.335. The omission was surface-level alignment.

  2. *Claude

Probe: LIVE: Trump says Iran deal not ‘fully negotiated yet’

Void words injected: arms deal, realdonaldtrump, peace deal, trumped, trumpcare Mean max cliff: 0.1827 Phase shifts (broke under pressure): ChatGPT, Claude, Gemini, DeepSeek

Cliff table (cosine distance per step):

  • Gemini: baseline→step1 0.2110 step1→step2 0.1356 step2→step3 0.1003 trigger: step_0_1 ← PHASE SHIFT
  • ChatGPT: baseline→step1 0.2072 step1→step2 0.1285 step2→step3 0.1729 trigger: step_0_1 ← PHASE SHIFT
  • Claude: baseline→step1 0.1893 step1→step2 0.1239 step2→step3 0.1372 trigger: step_0_1 ← PHASE SHIFT
  • DeepSeek: baseline→step1 0.1760 step1→step2 0.0730 step2→step3 0.1106 trigger: step_0_1 ← PHASE SHIFT
  • Grok: baseline→step1 0.1302 step1→step2 0.0966 step2→step3 0.1072 trigger: step_0_1

Verdict: Based on the information provided:

  • Models that shifted at step 1 (void proximity): These models exhibited surface-level alignment omission.
    • Gemini
  • Models that held until step 3: No m

Cross-Story Patterns

Most frequently omitted concepts:

  • arms deal (1 stories, 33.3%)
  • realdonaldtrump (1 stories, 33.3%)
  • peace deal (1 stories, 33.3%)
  • terrorist (1 stories, 33.3%)
  • yousafzai (1 stories, 33.3%)
  • death toll (1 stories, 33.3%)
  • rawalpindi (1 stories, 33.3%)
  • icbm (1 stories, 33.3%)
  • icbms (1 stories, 33.3%)
  • sukhoi (1 stories, 33.3%)
  • airstrike (1 stories, 33.3%)

Most frequent Logos synthesis terms:

  • negotiations (1 stories)
  • negotiated (1 stories)
  • bargaining (1 stories)
  • negotiates (1 stories)
  • arms deal (1 stories)
  • bombings (1 stories)
  • bombing (1 stories)
  • terrorist (1 stories)
  • terrorism (1 stories)
  • terrorists (1 stories)

Dual-channel confirmed (void + Logos independently converge): arms deal, terrorist

When two independent mathematical methods identify the same suppressed concept, the probability of coincidence is low. These are the strongest signals in the ledger.

Measurement layers: consensus density, geometric VIX, spectral resonance, SVD tomography, lexical void, Logos synthesis, atomic claim extraction, SVD null space projection, Wild Weasel 4-step, void vector, void clustering, token entropy Generated by EigenTrace at 2026-05-25 00:00 UTC Models: ChatGPT (GPT-5.4-mini), Claude (Sonnet 4), Gemini (3.1 Pro), DeepSeek (V3.2), Grok (4.1) Source: github.com/sdad1018/Eigentrace | eigentrace.ai